Object fingerprinting

Abstract

To allow tracking of vehicles across large stretches of highway, it is necessary to use multiple cameras. The usage of such camera networks poses the problem of accurately reacquiring each individual vehicle, as it leaves the receptive field of the one camera, and enters the other. The usage of low cost, low resolution cameras do not allow for license plate recognition. Therefore, a purely vision based solution to this problem is to extract visual features from each vehicle to create an object fingerprint. This fingerprint can then be used to reidentify vehicles as they enter the next camera's image. In this thesis several computer vision methods are explored for their ability to tackle the object fingerprinting problem. Moreover, an ensemble of those methods is created that surpasses the performance of the best individual technique.